Uncertainty Analysis for Computationally Expensive Models with Multiple Outputs

Bayesian MCMC calibration and uncertainty analysis for computationally expensive models is implemented using the SOARS (Statistical and Optimization Analysis using Response Surfaces) methodology. SOARS uses a radial basis function interpolator as a surrogate, also known as an emulator or meta-model,...

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Bibliographic Details
Published in:Journal of agricultural, biological, and environmental statistics biological, and environmental statistics, 2012-12, Vol.17 (4), p.623-640
Main Authors: Ruppert, David, Shoemaker, Christine A., Wang, Yilun, Li, Yingxing, Bliznyuk, Nikolay
Format: Article
Language:English
Subjects:
Agriculture
Agronomy. Soil science and plant productions
Algorithms
Analysis
Animal, plant and microbial ecology
Approximation
Biological and medical sciences
Biometrics, statistics, experimental designs, modeling, agricultural computer applications
Biostatistics
Calibration
Case studies
Computer analysis
Creeks
Evaluation points
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Generalities. Biometrics, experimentation. Remote sensing
Health Sciences
Markov processes
Mathematical optimization
Mathematics and Statistics
Medicine
Methods and techniques (sampling, tagging, trapping, modelling...)
Modeling
Monitoring/Environmental Analysis
Monte Carlo method
Parametric models
Phosphorus
Simulations
Statistics
Statistics for Life Sciences
Watersheds
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Summary:Bayesian MCMC calibration and uncertainty analysis for computationally expensive models is implemented using the SOARS (Statistical and Optimization Analysis using Response Surfaces) methodology. SOARS uses a radial basis function interpolator as a surrogate, also known as an emulator or meta-model, for the logarithm of the posterior density. To prevent wasteful evaluations of the expensive model, the emulator is built only on a high posterior density region (HPDR), which is located by a global optimization algorithm. The set of points in the HPDR where the expensive model is evaluated is determined sequentially by the GRIMA algorithm described in detail in another paper but outlined here. Enhancements of the GRIMA algorithm were introduced to improve efficiency. A case study uses an eight-parameter SWAT2 005 (Soil and Water Assessment Tool) model where daily stream flows and phosphorus concentrations are modeled for the Town Brook watershed which is part of the New York City water supply. A Supplemental Material file available online contains additional technical details and additional analysis of the Town Brook application.
ISSN:1085-7117
1537-2693
DOI:10.1007/s13253-012-0091-0